[jira] [Comment Edited] (SYSTEMML-969) Add Vector As Supported Type In Frame Conversions

["Matthias Boehm (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SYSTEMML-969?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15534945#comment-15534945 ] 

Matthias Boehm edited comment on SYSTEMML-969 at 9/30/16 4:03 AM:
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ok, thanks again for pointing out this missing functionality. We now support dataframe-frame conversions with mixed schemas that include vector columns. We make one simplifying assumption though: we only allow a single vector column in the schema (but at arbitrary positions and mixed with arbitrary scalar fields) because this allows us to handle schema information without looking at the data (for the vector sizes).


was (Author: mboehm7):
ok, thanks again for pointing out this missing functionality. We now support dataframe-frame conversions with mixed schemas that include vector columns. We make one simplifying assumption through: we only allow a single vector column in the schema (at arbitrary positions and mixed with arbitrary scalar fields) because this allows us to handle schema information without looking at the data (for the vector sizes).

> Add Vector As Supported Type In Frame Conversions
> -------------------------------------------------
>
>                 Key: SYSTEMML-969
>                 URL: https://issues.apache.org/jira/browse/SYSTEMML-969
>             Project: SystemML
>          Issue Type: New Feature
>            Reporter: Mike Dusenberry
>             Fix For: SystemML 0.11
>
>
> Currently, we are able to pass in Spark DataFrames with Vector type columns as input to SystemML scripts to be converted to a SystemML {{matrix}}.  We should add the Vector type to the {{frame}} conversion code too.
> Example:  Given a Spark DataFrame of schema <double, vector, string>, we should be able to convert that to a SystemML {{frame}} with a bunch of double columns and the final string column.
> cc [~mboehm7], [~acs_s]



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